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NetData vs Prometheus: What are the differences?
NetData and Prometheus are two popular monitoring tools that provide insights into the performance and health of systems, applications, and networks. Let's explore the key differences between them.
Data Collection Method: NetData uses a streaming-based approach to collect data in real-time, continuously polling system metrics at high frequencies. On the other hand, Prometheus follows a pull-based model, where it regularly scrapes metrics from endpoint targets. This fundamental difference in data collection methods can affect the accuracy and responsiveness of the monitoring data.
Architecture: NetData has an agent-based architecture, which means that individual agents need to be installed and configured on each target machine. In contrast, Prometheus operates as a standalone server that collects metrics from various exporters and targets through HTTP or other protocols. This architectural difference can impact the deployment and scalability of the monitoring setup.
Alerting and Notification: NetData supports basic alerting capabilities but relies on external tools like email or SMS gateways for notifications. Prometheus, on the other hand, provides a built-in alerting system that can trigger notifications based on user-defined rules and thresholds. This native alerting feature makes Prometheus more self-contained and convenient for managing alerts.
Data Storage: NetData stores metrics in memory by default, allowing for real-time visualization and analysis. However, for long-term storage or historical analysis, NetData relies on third-party tools like Elasticsearch or InfluxDB. In contrast, Prometheus has its own time-series database that stores metrics persistently, making it easier to perform time-based queries and generate historical reports.
Service Discovery: NetData does not have built-in service discovery mechanisms and relies on manual configuration of targets. On the other hand, Prometheus has robust service discovery capabilities that automatically identify and monitor new instances as they come online or go offline. This automatic service discovery simplifies the management of dynamic environments and facilitates scaling.
Ecosystem and Integrations: Prometheus has a vibrant ecosystem with a wide range of integrations, exporters, and community-contributed plugins, making it easy to collect metrics from different systems and applications. NetData, while extensible through various collectors and plugins, has a less extensive ecosystem and may require more custom development for integrating with specific technologies.
In summary, NetData provides real-time, per-second monitoring with a user-friendly interface, making it easy to visualize system metrics and troubleshoot issues quickly. In contrast, Prometheus offers powerful querying and alerting capabilities, along with a robust ecosystem of exporters and integrations, making it suitable for large-scale, multi-dimensional monitoring setups.
Looking for a tool which can be used for mainly dashboard purposes, but here are the main requirements:
- Must be able to get custom data from AS400,
- Able to display automation test results,
- System monitoring / Nginx API,
- Able to get data from 3rd parties DB.
Grafana is almost solving all the problems, except AS400 and no database to get automation test results.
You can look out for Prometheus Instrumentation (https://prometheus.io/docs/practices/instrumentation/) Client Library available in various languages https://prometheus.io/docs/instrumenting/clientlibs/ to create the custom metric you need for AS4000 and then Grafana can query the newly instrumented metric to show on the dashboard.
Hi, We have a situation, where we are using Prometheus to get system metrics from PCF (Pivotal Cloud Foundry) platform. We send that as time-series data to Cortex via a Prometheus server and built a dashboard using Grafana. There is another pipeline where we need to read metrics from a Linux server using Metricbeat, CPU, memory, and Disk. That will be sent to Elasticsearch and Grafana will pull and show the data in a dashboard.
Is it OK to use Metricbeat for Linux server or can we use Prometheus?
What is the difference in system metrics sent by Metricbeat and Prometheus node exporters?
Regards, Sunil.
If you're already using Prometheus for your system metrics, then it seems like standing up Elasticsearch just for Linux host monitoring is excessive. The node_exporter is probably sufficient if you'e looking for standard system metrics.
Another thing to consider is that Metricbeat / ELK use a push model for metrics delivery, whereas Prometheus pulls metrics from each node it is monitoring. Depending on how you manage your network security, opting for one solution over two may make things simpler.
Hi Sunil! Unfortunately, I don´t have much experience with Metricbeat so I can´t advise on the diffs with Prometheus...for Linux server, I encourage you to use Prometheus node exporter and for PCF, I would recommend using the instana tile (https://www.instana.com/supported-technologies/pivotal-cloud-foundry/). Let me know if you have further questions! Regards Jose
We're looking for a Monitoring and Logging tool. It has to support AWS (mostly 100% serverless, Lambdas, SNS, SQS, API GW, CloudFront, Autora, etc.), as well as Azure and GCP (for now mostly used as pure IaaS, with a lot of cognitive services, and mostly managed DB). Hopefully, something not as expensive as Datadog or New relic, as our SRE team could support the tool inhouse. At the moment, we primarily use CloudWatch for AWS and Pandora for most on-prem.
this is quite affordable and provides what you seem to be looking for. you can see a whole thing about the APM space here https://www.apmexperts.com/observability/ranking-the-observability-offerings/
I worked with Datadog at least one year and my position is that commercial tools like Datadog are the best option to consolidate and analyze your metrics. Obviously, if you can't pay the tool, the best free options are the mix of Prometheus with their Alert Manager and Grafana to visualize (that are complementary not substitutable). But I think that no use a good tool it's finally more expensive that use a not really good implementation of free tools and you will pay also to maintain its.
The objective of this work was to develop a system to monitor the materials of a production line using IoT technology. Currently, the process of monitoring and replacing parts depends on manual services. For this, load cells, microcontroller, Broker MQTT, Telegraf, InfluxDB, and Grafana were used. It was implemented in a workflow that had the function of collecting sensor data, storing it in a database, and visualizing it in the form of weight and quantity. With these developed solutions, he hopes to contribute to the logistics area, in the replacement and control of materials.
Pros of Netdata
- Free17
- Easy setup14
- Graphs are interactive12
- Montiors datasbases9
- Well maintained on github9
- Monitors nginx, redis, logs8
- Can submit metrics to Time Series databases4
- Open source3
- Easy Alert Setop2
- Netdata is also a statsd server2
- Written in C1
- GPLv31
- Zabbix0
Pros of Prometheus
- Powerful easy to use monitoring47
- Flexible query language38
- Dimensional data model32
- Alerts27
- Active and responsive community23
- Extensive integrations22
- Easy to setup19
- Beautiful Model and Query language12
- Easy to extend7
- Nice6
- Written in Go3
- Good for experimentation2
- Easy for monitoring1
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Cons of Netdata
Cons of Prometheus
- Just for metrics12
- Bad UI6
- Needs monitoring to access metrics endpoints6
- Not easy to configure and use4
- Supports only active agents3
- Written in Go2
- TLS is quite difficult to understand2
- Requires multiple applications and tools2
- Single point of failure1
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